Paper Citation Record · LEDGER

MoMo: Momentum Models for Adaptive Learning Rates

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2305.07583.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2305.07583 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T17:16:59.185567Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-03T17:08:43.630762Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation f8857d48-a2fb-4254-9c28-a875520e6653 · inbound

Polyak Stepsize: Estimating Optimal Functional Values Without Parameters or Prior Knowledge cites this paper.

Polyak Stepsize: Estimating Optimal Functional Values Without Parameters or Prior Knowledge MoMo: Momentum Models for Adaptive Learning Rates

Reference 1969

Resolution: unresolved; no resolver link, observed 2026-08-15T17:16:59.185567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e5b5d8d5-cf21-4b7d-b710-6abd3ee3f831 · inbound

Adaptive Memory Momentum via a Model-Based Framework for Deep Learning Optimization cites this paper.

Adaptive Memory Momentum via a Model-Based Framework for Deep Learning Optimization MoMo: Momentum Models for Adaptive Learning Rates

Reference 57

Resolution: verified exact; arxiv_id, observed 2026-05-18T09:46:12.541220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6eecfa10-1506-4669-90a7-06e49abd6c73 · inbound

Gradient Clipping Beyond Vector Norms: A Spectral Approach for Matrix-Valued Parameters cites this paper.

Gradient Clipping Beyond Vector Norms: A Spectral Approach for Matrix-Valued Parameters MoMo: Momentum Models for Adaptive Learning Rates

Reference 54

Resolution: verified exact; arxiv_id, observed 2026-05-13T07:02:27.347009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation df465041-dd4a-480a-8533-71e5089bf850 · inbound

Zero-order Parameter-free Optimization for LMO-based Methods: Novel Approach for Efficient Fine-tuning cites this paper.

Zero-order Parameter-free Optimization for LMO-based Methods: Novel Approach for Efficient Fine-tuning MoMo: Momentum Models for Adaptive Learning Rates

Reference 57

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T17:08:43.632251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.